Medical image diagnosis apparatus and management apparatus

ABSTRACT

A medical image diagnosis apparatus according to an embodiment includes obtaining circuitry, detecting circuitry, deriving circuitry, and controlling circuitry. The obtaining circuitry is configured to obtain image data of a patient. The detecting circuitry is configured to detect each of a plurality of sites of the patient from the image data. The deriving circuitry is configured to derive information about a structuring member in the patient, on the basis of a detection result obtained by the detecting circuitry. The controlling circuitry is configured to determine an injection condition for a contrast agent to be administered to the patient for a contrast-enhanced scan, on the basis of the information about the structuring member.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is based upon and claims the benefit of priority fromJapanese Patent Application No. 2016-094099, filed on May 9, 2016 andJapanese Patent Application No. 2017-091270, filed on May 1, 2017; theentire contents of which are incorporated herein by reference.

FIELD

Embodiments described herein relate generally to a medical imagediagnosis apparatus and a management apparatus.

BACKGROUND

Conventionally, during a medical examination using an X-ray ComputedTomography (CT) apparatus, in some situations, a contrast-enhanced scanmay be performed by administering a contrast agent to the examinedsubject (hereinafter “patient”). In those situations, the X-ray CTapparatus determines an injection condition for a contrast agent to beadministered to the patient, on the basis of the height, the weight, aBody Mass Index (BMI) and/or the like of the patient.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram illustrating an exemplary configuration of a medicalinformation processing system according to a first embodiment;

FIG. 2 is a diagram illustrating an exemplary configuration of an X-rayCT apparatus according to the first embodiment;

FIG. 3 is a drawing for explaining a three-dimensional scanogram imagetaking process performed by scan controlling circuitry according to thefirst embodiment;

FIG. 4A is a drawing for explaining an example of a site detectingprocess performed by a detecting function according to the firstembodiment;

FIG. 4B is another drawing for explaining the example of the sitedetecting process performed by the detecting function according to thefirst embodiment;

FIG. 5 is a table for explaining the example of the site detectingprocess performed by the detecting function according to the firstembodiment;

FIG. 6 is yet another drawing for explaining the example of the sitedetecting process performed by the detecting function according to thefirst embodiment;

FIG. 7 is a drawing illustrating an example of a virtual patient imagestored in storage circuitry according to the first embodiment;

FIG. 8 is a drawing for explaining an example of a matching processperformed by a position matching function according to the firstembodiment;

FIG. 9 is a drawing illustrating an example of a scan rangetransformation process using a coordinate transformation according tothe first embodiment;

FIG. 10 is a drawing for explaining the first embodiment;

FIG. 11 is a flowchart illustrating a procedure in a process performedby the X-ray CT apparatus according to the first embodiment;

FIG. 12 is a drawing for explaining a second embodiment; and

FIG. 13 is a drawing for explaining another embodiment.

DETAILED DESCRIPTION

Exemplary embodiments of a medical image diagnosis apparatus and amanagement apparatus will be explained in detail below, with referenceto the accompanying drawings. In the following sections, a medicalinformation processing system including an X-ray Computed Tomography(CT) apparatus will be explained as an example. In a medical informationprocessing system 100 in FIG. 1, only one server apparatus and oneterminal apparatus are illustrated; however, in actuality, the systemmay include two or more server apparatuses and/or two or more terminalapparatuses. Further, for example, the medical information processingsystem 100 may also include one or more medical image diagnosisapparatuses such as X-ray diagnosis apparatuses, Magnetic ResonanceImaging (MRI) apparatuses, ultrasound diagnosis apparatuses, and/or thelike.

First Embodiment

FIG. 1 is a diagram illustrating an exemplary configuration of themedical information processing system 100 according to a firstembodiment. As illustrated in FIG. 1, the medical information processingsystem 100 according to the first embodiment includes an X-ray CTapparatus 1, a server apparatus 2, and a terminal apparatus 3. The X-rayCT apparatus 1, the server apparatus 2, and the terminal apparatus 3 arein a state of being able to communicate with one another either directlyor indirectly via, for example, an intra-hospital Local Area Network(LAN) installed in a hospital. For example, when a Picture Archiving andCommunication System (PACS) is introduced into the medical informationprocessing system 100, the apparatuses are configured to transmit andreceive medical images and the like to and from one another according tothe Digital Imaging and Communication in Medicine (DICOM) standard.

Further, a Hospital Information System (HIS) or a Radiology InformationSystem (RIS), for example, is introduced into the medical informationprocessing system 100 so as to manage various types of information. Forexample, the terminal apparatus 3 transmits a medical examination ordergenerated in accordance with the system described above, to the X-ray CTapparatus 1 and to the server apparatus 2. The X-ray CT apparatus 1obtains patient information either from the medical examination orderdirectly received from the terminal apparatus 3 or from a patient list(a modality work list) generated in correspondence with each modality bythe server apparatus 2 that received the medical examination order. TheX-ray CT apparatus 1 further acquires X-ray CT image data for eachpatient. After that, the X-ray CT apparatus 1 transmits the acquiredX-ray CT image data and image data generated by performing any ofvarious types of image processing processes on the X-ray CT image data,to the server apparatus 2. The server apparatus 2 stores therein theX-ray CT image data and the image data received from the X-ray CTapparatus 1, and also, generates image data from the X-ray CT imagedata, and transmits any of the image data to the terminal apparatus 3 inresponse to an obtainment request from the terminal apparatus 3. Theterminal apparatus 3 displays the image data received from the serverapparatus 2 on a monitor or the like. The following sections describeeach of the apparatuses.

The terminal apparatus 3 is an apparatus provided in each medicaldepartment in the hospital and is operated by medical doctors working invarious medical departments. The terminal apparatus 3 may be a PersonalComputer (PC) a tablet-type PC, a Personal Digital Assistant (PDA), amobile phone, or the like. For example, to the terminal apparatus 3,medical doctors input medical chart information including patients'symptoms and medical doctors' observations. Further, to the terminalapparatus 3, a medical examination order to order a medical examinationusing the X-ray CT apparatus 1 is input. The terminal apparatus 3transmits the input medical examination order to the X-ray CT apparatus1 and to the server apparatus 2. In other words, each of the medicaldoctors working in the medical departments operates the terminalapparatus 3 so as to read reception information and electronic chartinformation of each patient who came to the hospital, gives aconsultation to his/her patients, and inputs medical chart informationto a read electronic chart. After that, each of the medical doctorsworking in the medical departments transmits a medical examination orderby operating the terminal apparatus 3, depending on whether or not amedical examination using the X-ray CT apparatus 1 is required.

The server apparatus 2 is an apparatus configured to store thereinmedical images acquired by a medical image diagnosis apparatus (e.g.,the X-ray CT image data and the image data acquired by the X-ray CTapparatus 1) and to perform various types of image processing processeson the medical images. For example, the server apparatus 2 may beconfigured by using a PACS server. For example, the server apparatus 2is configured to receive a plurality of medical examination orders fromthe terminal apparatus 3 provided in each of the medical departments, togenerate a patient list for each medical image diagnosis apparatus, andto transmit each of the generated patient lists to a corresponding oneof the medical image diagnosis apparatuses. In one example, the serverapparatus 2 receives medical examination orders for performing medicalexaminations by using the X-ray CT apparatus 1 from the terminalapparatus 3 provided in each medical department, generates patientlists, and transmits the generated patient lists to the X-ray CTapparatus 1. After that, the server apparatus 2 stores therein the X-rayCT image data and the image data acquired by the X-ray CT apparatus 1and further transmits the X-ray CT image data and the image data to theterminal apparatus 3, in response to an obtainment request from theterminal apparatus 3.

The X-ray CT apparatus 1 is configured to acquire the X-ray CT imagedata from each patient and to transmit the acquired X-ray CT image dataand the image data generated by performing any of the various types ofimage processing processes on the X-ray CT image data, to the serverapparatus 2. FIG. 2 is a diagram illustrating an exemplary configurationof the X-ray CT apparatus 1 according to the first embodiment. Asillustrated in FIG. 2, the X-ray CT apparatus 1 according to the firstembodiment includes a gantry 10, a couch 20, and a console 30. Further,the X-ray CT apparatus 1 is connected to a contrast agent injector (notillustrated in FIG. 2).

The gantry 10 is a device configured to radiate X-rays onto an examinedsubject P (the patient), to detect X-rays that have passed through thepatient P, and to output a result of the detection to the console 30.The gantry 10 includes X-ray radiation controlling circuitry 11, anX-ray generating device 12, a detector 13, and data acquiring circuitry(a Data Acquisition System [DAS]) 14, a rotating frame 15, and gantrydriving circuitry 16. The data acquiring circuitry 14 is an example ofobtaining circuitry.

The rotating frame 15 is an annular frame configured to support theX-ray generating device 12 and the detector 13 so as to oppose eachother while the patient P is interposed therebetween and configured tobe rotated by the gantry driving circuitry 16 (explained later) at ahigh speed on a circular orbit centered on the patient P.

The X-ray radiation controlling circuitry 11 is a device configured, asa high-voltage generating unit, to supply a high voltage to an X-raytube 12 a. The X-ray tube 12 a is configured to generate X-rays by usingthe high voltage supplied thereto from the X-ray radiation controllingcircuitry 11. The X-ray radiation controlling circuitry 11 is configuredto adjust the X-ray dose radiated onto the patient P, by adjusting theX-ray tube voltage and the X-ray tube current supplied to the X-ray tube12 a, under control of scan controlling circuitry 33 (explained later).

Further, the X-ray radiation controlling circuitry 11 is configured toperform a switching process on a wedge 12 b. Further, by adjusting theopening degree of a collimator 12 c, the X-ray radiation controllingcircuitry 11 is configured to adjust the radiation range (a fan angle ora cone angle) of the X-rays. In the present embodiments, an arrangementis acceptable in which an operator manually switches among a pluralityof types of wedges.

The X-ray generating device 12 is a device configured to generate theX-rays and to radiate the generated X-rays onto the patient P. The X-raygenerating device 12 includes the X-ray tube 12 a, the wedge 12 b, andthe collimator 12 c.

The X-ray tube 12 a is a vacuum tube configured to radiate an X-ray beamonto the patient P by using the high voltage supplied thereto by thehigh-voltage generating unit (not illustrated). The X-ray tube 12 aradiates the X-ray beam onto the patient P, as the rotating frame 15rotates. The X-ray tube 12 a is configured to generate the X-ray beamthat spreads with the fan angle or the cone angle. For example, underthe control of the X-ray radiation controlling circuitry 11, the X-raytube 12 a is capable of continuously emitting X-rays in the entiresurrounding of the patient P to realize a full reconstruction processand is capable of continuously emitting X-rays in an emission range (180degrees+the fan angle) that enables a half reconstruction to realize ahalf reconstruction process. Further, under the control of the X-rayradiation controlling circuitry 11, the X-ray tube 12 a is capable ofintermittently emitting X-rays (pulse X-rays) in positions (X-ray tubepositions) set in advance. Further, the X-ray radiation controllingcircuitry 11 is also capable of modulating the intensities of the X-raysemitted from the X-ray tube 12 a. For example, the X-ray radiationcontrolling circuitry 11 increases the intensities of the X-rays emittedfrom the X-ray tube 12 a in a specific X-ray tube position and decreasesthe intensities of the X-rays emitted from the X-ray tube 12 a in arange other than the specific X-ray tube position.

The wedge 12 b is an X-ray filter configured to adjust the X-ray dose ofthe X-rays emitted from the X-ray tube 12 a. More specifically, thewedge 12 b is a filter configured to pass and attenuate the X-raysemitted from the X-ray tube 12 a, so that the X-rays radiated from theX-ray tube 12 a onto the patient P have a predetermined distribution.For example, the wedge 12 b is a filter obtained by processing aluminumso as to have a predetermined target angle and a predeterminedthickness. The wedge may be referred to as a wedge filter or a bow-tiefilter.

The collimator 12 c is a slit configured to narrow down the radiationrange of the X-rays of which the X-ray dose has been adjusted by thewedge 12 b, under the control of the X-ray radiation controllingcircuitry 11 (explained later).

The gantry driving circuitry 16 is configured to cause the X-raygenerating device 12 and the detector 13 to revolve on the circularorbit centered on the patient P, by driving the rotating frame 15 torotate.

The detector 13 is a two-dimensional array detector (a planar detector)configured to detect the X-rays that have passed through the patient P.In the detector 13, a plurality of rows of detecting elements arearranged along the body-axis direction of the patient P (i.e., theZ-axis direction in FIG. 2), while each row contains a plurality ofX-ray detecting elements corresponding to a plurality of channels. Morespecifically, the detector 13 according to the first embodiment includesthe X-ray detecting elements that are arranged in a large number of rows(e.g., 320 rows) along the body-axis direction of the patient P. Forexample, the detector 13 is capable of detecting X-rays that have passedthrough the patient P in a wide range such as a range including thelungs or the heart of the patient P.

The data acquiring circuitry 14 is configured with the DAS and isconfigured to acquire projection data from X-ray detection data detectedby the X-ray detector 13. For example, the data acquiring circuitry 14generates the projection data by performing an amplifying process, anAnalog/Digital (A/D) converting process, a sensitivity correctingprocess among the channels, and/or the like on X-ray intensitydistribution data detected by the detector 13 and further transmits thegenerated projection data to the console 30 (explained later). Forexample, when X-rays are continuously emitted from the X-ray tube 12 awhile the rotating frame 15 is rotating, the data acquiring circuitry 14acquires a group of projection data corresponding to the entiresurrounding (corresponding to 360 degrees). Further, the data acquiringcircuitry 14 transmits the acquired pieces of projection data to theconsole 30 (explained later), while keeping the pieces of projectiondata in correspondence with the X-ray tube positions. The X-ray tubepositions serve as information indicating projection directions of thepieces of projection data. Alternatively, the sensitivity correctingprocess among the channels may be performed by pre-processing circuitry34 (explained later).

The couch 20 is a device on which the patient P is placed and includes acouch driving device 21 and a couchtop 22, as illustrated in FIG. 2. Thecouch driving device 21 is configured to move the patient P into therotating frame 15 by moving the couchtop 22 in the Z-axis direction. Thecouchtop 22 is a board on which the patient P is placed.

For example, the gantry 10 performs a helical scan by which the patientP is helically scanned by causing the rotating frame 15 to rotate whilethe couchtop 22 is being moved. In another example, the gantry 10performs a conventional scan by which the patient P is scanned on acircular orbit by causing the rotating frame 15 to rotate, while theposition of the patient P is being fixed after the couchtop 22 is moved.In yet another example, the gantry 10 implements a step-and-shoot methodby which the conventional scan is performed in multiple scan areas, bymoving the position of the couchtop 22 at regular intervals.

The console 30 is a device configured to receive operations performed bythe operator on the X-ray CT apparatus 1 and also configured toreconstruct X-ray CT image data by using the projection data acquired bythe gantry 10. As illustrated in FIG. 2, the console 30 includes inputcircuitry 31, a display 32, the scan controlling circuitry 33, thepre-processing circuitry 34, storage circuitry 35, image reconstructingcircuitry 36, and processing circuitry 37. The pre-processing circuitry34 and the image reconstructing circuitry 36 are each an example ofobtaining circuitry.

The input circuitry 31 includes a mouse, a keyboard, a trackball, aswitch, a button, a joystick, and/or the like used by the operator ofthe X-ray CT apparatus 1 to input various types of instructions andvarious types of settings. The input circuitry 31 is configured totransfer information about the instructions and the settings receivedfrom the operator to the processing circuitry 37. For example, the inputcircuitry 31 receives, from the operator, an image taking condition forthe X-ray CT image data, a reconstructing condition used when the X-rayCT image data is reconstructed, an image processing condition applied tothe X-ray CT image data, and the like. Further, the input circuitry 31also receives an operation to select a medical examination to beperformed on the patient P. In addition, the input circuitry 31 receivesa designation operation to designate a site rendered in an image.

The display 32 is a monitor referenced by the operator and is configuredto display the image data generated from the X-ray CT image data for theoperator and to display a Graphical User Interface (GUI) used forreceiving the various types of instructions and the various types ofsettings from the operator via the input circuitry 31, under control ofthe processing circuitry 37. Further, the display 32 is also configuredto display a planning screen for a scan plan and a screen of imagesduring a scan. Further, the display 32 is configured to display avirtual patient image, image data, or the like including X-ray exposureinformation. The virtual patient image displayed by the display 32 willbe explained in detail later.

Under the control of the processing circuitry 37, the scan controllingcircuitry 33 is configured to control the projection data acquiringprocess performed by the gantry 10, by controlling operations of theX-ray radiation controlling circuitry 11, the gantry driving circuitry16, the data acquiring circuitry 14, and the couch driving device 21.More specifically, the scan controlling circuitry 33 is configured tocontrol projection data acquiring processes during an image takingprocess to acquire a position determining image (a scanogram image) andduring a main image taking process (a scan) to acquire an image used fora diagnosis purpose. In the present example, the X-ray CT apparatus 1according to the first embodiment is configured so as to be able to takea two-dimensional scanogram image and a three-dimensional scanogramimage.

For example, by continuously taking images while moving the couchtop 22at a constant speed and having the X-ray tube 12 a fixed in the positioncorresponding to 0 degrees (a straight-on position of the patient P),the scan controlling circuitry 33 takes the two-dimensional scanogramimage. Alternatively, by intermittently moving the couchtop 22 while theX-ray tube 12 a is fixed in the position corresponding to 0 degrees, thescan controlling circuitry 33 may take the two-dimensional scanogramimage by repeatedly taking images intermittently in synchronization withthe moving of the couchtop. In the present example, the scan controllingcircuitry 33 is capable of taking the position determining image, notonly from the straight-on direction of the patient P, but also from anyarbitrary direction (e.g., a lateral direction).

Further, by acquiring the projection data corresponding to the entiresurrounding of the patient P during a scanogram image taking process,the scan controlling circuitry 33 takes the three-dimensional scanogramimage. FIG. 3 is a drawing for explaining a three-dimensional scanogramimage taking process performed by the scan controlling circuitry 33according to the first embodiment. For example, as illustrated in FIG.3, the scan controlling circuitry 33 acquires the projection datacorresponding to the entire surrounding of the patient P, by performingeither a helical scan or a non-helical scan. In this situation, the scancontrolling circuitry 33 performs the helical scan or the non-helicalscan on a wide range such as the entire chest, the entire abdomen, theentire upper body, or the entire body of the patient P, by using anX-ray dose smaller than that used in the main image taking process. Toperform the non-helical scan, for example, a scan is performed byimplementing the step-and-shoot method described above.

When the scan controlling circuitry 33 has acquired the projection datacorresponding to the entire surrounding of the patient P in this manner,the image reconstructing circuitry 36 (explained later) is able toreconstruct three-dimensional X-ray CT image data (volume data), and itis therefore possible to generate a position determining image from anarbitrary direction, by using the reconstructed volume data, asillustrated in FIG. 3. In this situation, whether the positiondetermining image is taken two-dimensionally or three-dimensionally mayarbitrarily be set by the operator or may be set in advance inaccordance with specifics of the medical examination.

Returning to the description of FIG. 2, the pre-processing circuitry 34is configured to generate corrected projection data by performing alogarithmic converting process as well as correcting processes such asan offset correcting process, a sensitivity correcting process, a beamhardening correcting process, and the like, on the projection datagenerated by the data acquiring circuitry 14. More specifically, thepre-processing circuitry 34 generates pieces of corrected projectiondata both for the projection data of the position determining image andfor the projection data acquired by performing the main image takingprocess that were generated by the data acquiring circuitry 14 andfurther stores the pieces of corrected projection data into the storagecircuitry 35.

The storage circuitry 35 is configured to store therein the projectiondata generated by the pre-processing circuitry 34. More specifically,the storage circuitry 35 stores therein the projection data of theposition determining image and the projection data for the diagnosispurpose acquired by performing the main image taking process that weregenerated by the pre-processing circuitry 34. Further, the storagecircuitry 35 is configured to store therein image data generated by theimage reconstructing circuitry 36 (explained later), the virtual patientimage, and the like. Further, the storage circuitry 35 is configured tostore therein a processing result obtained by the processing circuitry37 (explained later), as appropriate. The virtual patient image and theprocessing result obtained by the processing circuitry 37 will beexplained later.

The image reconstructing circuitry 36 is configured to reconstruct theX-ray CT image data by using the projection data stored in the storagecircuitry 35. More specifically, the image reconstructing circuitry 36reconstructs pieces of X-ray CT image data both from the projection dataof the position determining image and the projection data of the imagefor the diagnosis purpose. In this situation, any of various methods canbe used as the reconstructing method. For example, a back projectionprocess may be used. Further, examples of the back projection processinclude a back projection process using a Filtered Back Projection (FBP)method. Alternatively, the image reconstructing circuitry 36 mayreconstruct the X-ray CT image data by using a successive approximationmethod.

Further, the image reconstructing circuitry 36 is configured to generateimage data by performing various types of image processing processes onthe X-ray CT image data. After that, the image reconstructing circuitry36 stores the reconstructed X-ray CT image data and the image datagenerated by performing the various types of image processing processes,into the storage circuitry 35.

The processing circuitry 37 is configured to exercise overall control ofthe X-ray CT apparatus 1 by controlling operations of the gantry 10, thecouch 20, and the console 30. More specifically, the processingcircuitry 37 is configured to control a CT scan performed by the gantry10, by controlling the scan controlling circuitry 33. Also, theprocessing circuitry 37 is configured to control the imagereconstructing process and the image generating process performed by theconsole 30, by controlling the image reconstructing circuitry 36.Further, the processing circuitry 37 is configured to exercise controlso that the display 32 displays any of the various types image datastored in the storage circuitry 35.

Further, as illustrated in FIG. 2, the processing circuitry 37 isconfigured to execute a detecting function 37 a, a position matchingfunction 37 b, and a controlling function 37 c. In this situation, forexample, processing functions executed by the constituent elements ofthe processing circuitry 37 illustrated in FIG. 2, namely the functionssuch as the detecting function 37 a, the position matching function 37b, and the controlling function 37 c are recorded in the storagecircuitry 35 in the form of computer-executable programs. The processingcircuitry 37 is a processor configured to realize the functionscorresponding to the computer programs (hereinafter, “programs”), byreading the programs from the storage circuitry 35 and executing theread programs. In other words, the processing circuitry 37 that has readthe programs has the functions illustrated within the processingcircuitry 37 in FIG. 2. The detecting function 37 a is an example ofdetecting circuitry. The controlling function 37 c is an example ofderiving circuitry and controlling circuitry.

The detecting function 37 a is configured to detect each of a pluralityof sites of the patient P from the three-dimensional image data. Morespecifically, the detecting function 37 a detects a site such as anorgan included in the three-dimensional X-ray CT image data (the volumedata) reconstructed by the image reconstructing circuitry 36. Forexample, with respect to at least one selected from between the volumedata of the position determining image and the volume data of the imagefor the diagnosis purpose, the detecting function 37 a detects the sitesuch as an organ on the basis of anatomical feature points calledanatomical landmarks. In the present example, the term “anatomicallandmark” denotes a point indicating a feature of a site such as aspecific bone, organ, blood vessel, nerve, or lumen. In other words, bydetecting the anatomical landmark of a specific organ, bone, or thelike, the detecting function 37 a detects the bone, organ, blood vessel,nerve, lumen, or the like included in the volume data. Further, bydetecting the landmark (the feature point) characteristic to humanbodies, the detecting function 37 a is also capable of detecting thepositions of the head, the neck, the chest, the abdomen, the legs,and/or the like included in the volume data. The “sites” used in thedescription of the present embodiments include any of these positions,in addition to bones, organs, blood vessels, nerves, lumens, and thelike. In the following sections, an example of a site detecting processperformed by the detecting function 37 a will be explained. The “sitedetecting process” performed by the detecting function 37 a may also bereferred to as an “AL analysis”.

For example, with respect to either the volume data of the positiondetermining image or the volume data of the image for the diagnosispurpose, the detecting function 37 a extracts the anatomical landmarkson the basis of voxel values included in the volume data. After that,the detecting function 37 a optimizes the positions of the landmarksextracted from the volume data, by eliminating inaccurate landmarks fromamong the landmarks extracted from the volume data, by comparing thethree-dimensional positions of the anatomical landmarks based oninformation from textbooks and the like, with the positions of thelandmarks extracted from the volume data. As a result, the detectingfunction 37 a detects various sites of the patient P included in thevolume data. In one example, the detecting function 37 a extracts theanatomical landmarks included in the volume data, by using a supervisedmachine learning algorithm. In the present example, the supervisedmachine learning algorithm is structured by using a plurality of teacherimages in which correct anatomical landmarks are manually arranged. Thesupervised machine learning algorithm may be configured by using adecision forest, for example.

Further, the detecting function 37 a optimizes the extracted landmarksby comparing a model indicating three-dimensional positionalrelationships among anatomical landmarks of human bodies with theextracted landmarks. In the present example, the model is structured byusing the aforementioned teaching images and may be configured by usinga point distribution model, for example. In other words, the detectingfunction 37 a optimizes the landmarks by eliminating the inaccuratelandmarks, by comparing the model with the extracted landmarks, themodel defining the shapes of various sites, the positional relationshipsthereof, points unique to the sites, and the like on the basis of theplurality of teacher images in which the correct anatomical landmarksare manually arranged.

Next, an example of the site detecting process performed by thedetecting function 37 a will be explained, with reference to FIGS. 4A,4B, 5, and 6. FIGS. 4A, 4B, 5, and 6 are drawings for explainingexamples of the site detecting process performed by the detectingfunction 37 a according to the first embodiment. Although landmarks arearranged two-dimensionally in FIGS. 4A and 4B, the landmarks arearranged three-dimensionally in actuality. For example, by applying thesupervised machine learning algorithm to the volume data, the detectingfunction 37 a extracts voxels regarded as anatomical landmarks (the dotsin the drawing), as illustrated in FIG. 4A. Further, by fitting thepositions of the extracted voxels to a model defining shapes of varioussites, positional relationships thereof, points unique to the sites, andthe like, the detecting function 37 a extracts only such voxels thatcorrespond to more accurate landmarks, by eliminating inaccuratelandmarks from among the extracted voxels, as illustrated in FIG. 4B.

In this situation, the detecting function 37 a assigns identificationcodes for identifying the landmarks indicating the features of thesites, to the extracted landmarks (voxels) and further attachesinformation in which the identification codes are kept in correspondencewith position (coordinates) information of the landmarks to the imagedata, before storing the image data into the storage circuitry 35. Forexample, as illustrated in FIG. 4B, the detecting function 37 a assignsidentification codes such as C1, C2, and C3 to the extracted landmarks(voxels). In this situation, the detecting function 37 a attaches anidentification code to each of the pieces of data resulting from thedetecting process, before storing the pieces of data into the storagecircuitry 35. More specifically, the detecting function 37 a isconfigured to detect a site of the patient included in the volume datareconstructed from at least one selected from among: the projection dataof the position determining image; projection data acquired in anon-contrast-enhanced state; and projection data acquired while thecontrast is enhanced by a contrast agent.

For example, as illustrated in FIG. 5, the detecting function 37 aattaches information in which the identification codes are kept incorrespondence with the coordinates of the voxels detected from thevolume data of the position determining image (“position determining” inthe table) to the volume data, before storing the volume data into thestorage circuitry 35. In one example, the detecting function 37 aextracts the coordinates of landmark points from the volume data of theposition determining image and, as illustrated in FIG. 5, storesinformation such as “identification code: C1, coordinates (x₁,y₁,z₁)”and “identification code: C2, coordinates (x₂,y₂,z₂)” so as to be keptin correspondence with the volume data. As a result, the detectingfunction 37 a is able to identify what landmarks are present in whichpositions within the volume data of the position determining image. Thedetecting function 37 a is thus able to detect various sites such asorgans on the basis of these pieces of information.

Further, as illustrated in FIG. 5, for example, the detecting function37 a attaches information in which the identification codes are kept incorrespondence with the coordinates of the voxels detected from thevolume data of the diagnosis-purpose image (“scans” in the table) to thevolume data, before storing the volume data into the storage circuitry35. In this situation, during the scans, the detecting function 37 a isable to extract the coordinates of the landmark points from volume datain which the contrast is enhanced by a contrast agent(“contrast-enhanced phase” in the table) and from volume data in whichthe contrast is not enhanced by a contrast agent (“non-contrast-enhancedphase” in the table), so as to bring the identification codes intocorrespondence with the extracted coordinates.

In one example, from within the volume data of the diagnosis-purposeimage, the detecting function 37 a extracts the coordinates of thelandmark points from the volume data in the non-contrast-enhanced phaseand, as illustrated in FIG. 5, brings information such as“identification code C1, coordinates (x′₁,y′₁,z′₁)” and “identificationcode C2, coordinates (x′₂,y′₂,z′₂)” into correspondence with the volumedata, before storing the volume data. Further, from within the volumedata of the diagnosis-purpose image, the detecting function 37 aextracts the coordinates of the landmark points from the volume data inthe contrast-enhanced phase and, as illustrated in FIG. 5, bringsinformation such as “identification code C1, coordinates (x′₁,y′₁,z′₁)”and “identification code C2, coordinates (x′₂,y′₂,z′₂)” intocorrespondence with the volume data, before storing the volume data. Inthis situation, when the landmark points are extracted from the volumedata in the contrast-enhanced phase, the landmark points include one ormore landmark points that became extractable because of the contrastenhancement. For example, when extracting the landmark points from thevolume data in the contrast-enhanced phase, the detecting function 37 ais able to extract blood vessels and the like of which the contrast wasenhanced by the contrast agent. Accordingly, for the volume data in thecontrast-enhanced phase, as illustrated in FIG. 5, the detectingfunction 37 a brings identification codes C31, C32, C33, and C34 each ofwhich is used for identifying a different one of the blood vessels, intocorrespondence with the coordinates such as (x′₃₁,y′₃₁,z′₃₁) to(x′₃₄,y′₃₄,z′₃₄) of the landmark points represented by the blood vesselsand the like that were extracted as a result of the contrastenhancement.

As explained above, the detecting function 37 a is able to identify whatlandmark points are present in which positions within the volume data ofthe position determining image and of the diagnosis-purpose image. Thedetecting function 37 a is thus able to detect various sites such asorgans on the basis of these pieces of information. For example, byusing information about an anatomical positional relationship between atarget site subject to the detection and other sites positioned in thesurroundings of the target site, the detecting function 37 a detects theposition of the target site. In one example, when the target site is the“lungs”, the detecting function 37 a obtains coordinate information keptin correspondence with identification codes indicating features of thelungs and further obtains coordinate information kept in correspondencewith identification codes indicating sites positioned in thesurroundings of the “lungs”, such as the “ribs”, the “clavicles”, the“heart”, the “diaphragm”, and so on. Further, the detecting function 37a extracts a region of the “lungs” in the volume data by usinginformation about an anatomical positional relationship between the“lungs” and the sites in the surroundings thereof and the obtainedcoordinate information.

For example, the detecting function 37 a extracts a region R1corresponding to the “lungs” in the volume data, as illustrated in FIG.6, on the basis of information about positional relationships such as“the lung apices: 2 to 3 cm above the clavicles” and “the lower ends ofthe lungs: at the height of the seventh ribs”, as well as the coordinateinformation of the sites. In other words, the detecting function 37 aextracts the coordinate information of the voxels in the region R1within the volume data. The detecting function 37 a brings the extractedcoordinate information into correspondence with site information andfurther attaches these pieces of information to the volume data, beforestoring the volume data into the storage circuitry 35. Similarly, asillustrated in FIG. 6, the detecting function 37 a is also able toextract a region R2 corresponding to the “heart” in the volume data.

Further, on the basis of landmarks defining the positions of the headand the chest in the human body, the detecting function 37 a detectspositions included in the volume data. In this situation, it is possibleto arbitrarily define the positions of the head, the chest, and the likein the human body. For example, when the region from the seventhcervical vertebra to the lower ends of the lungs are defined as thechest, the detecting function 37 a detects a region from a landmarkcorresponding to the seventh cervical vertebra to a landmarkcorresponding to the lower ends of the lungs as the chest. In thissituation, the detecting function 37 a is capable of detecting sites byusing other various methods besides the abovementioned method using theanatomical landmarks. For example, the detecting function 37 a iscapable of detecting the sites included in the volume data byimplementing a region growing method based on voxel values, or the like.

The position matching function 37 b is configured to match the positionof each of the plurality of sites of the patient P included in thethree-dimensional image data with the position of each of a plurality ofsites in a human body included in virtual patient data. In thissituation, the virtual patient data is information indicating a standardposition of each of a plurality of sites in the human body. In otherwords, the position matching function 37 b matches the sites of thepatient P with the standard positions of the sites and further stores amatching result into the storage circuitry 35. For example, the positionmatching function 37 b matches the virtual patient image in which sitesin the human body are arranged in standard positions, with the volumedata of the patient P.

Next, the virtual patient image will be explained first. The virtualpatient image is generated in advance and stored in the storagecircuitry 35 as an image actually taken of a human body by using X-rays,the human body having a standard physique corresponding to a pluralityof combinations related to parameters with regard to physiques such asthe age, adult/child, male/female, the weight, and the height. In otherwords, the storage circuitry 35 stores therein data of a plurality ofvirtual patient images corresponding to the different combinations ofthe parameters presented above. In this situation, the virtual patientimages stored in the storage circuitry 35 are stored while being kept incorrespondence with anatomical landmarks (landmarks). For example, thehuman body has a large number of anatomical landmarks that can beextracted from images relatively easily on the basis of morphologicalfeatures thereof or the like, by performing an image processing processsuch as a pattern recognition process. The positions and positionalarrangements of the large number of anatomical landmarks in human bodiesare roughly fixed depending on physiques corresponding to ages,adult/child, male/female, the weights, and the heights.

The virtual patient images stored in the storage circuitry 35 are storedafter the large number of anatomical landmarks are detected in advance,and position data of the detected landmarks is either attached to orassociated with the data of the virtual patient images, together withthe respective identification codes of the landmarks. FIG. 7 is adrawing illustrating an example of the virtual patient images stored inthe storage circuitry 35 according to the first embodiment. For example,as illustrated in FIG. 7, the storage circuitry 35 stores therein avirtual patient image in which anatomical landmarks and identificationcodes such as “V1”, “V2”, “V3”, and so on used for identifying thelandmarks are kept in association with a three-dimensional human bodyincluding sites such as organs.

In other words, the storage circuitry 35 stores therein the coordinatesof the landmarks within a coordinate space of a three-dimensional humanbody image so as to be kept in association with the correspondingidentification codes. In one example, the storage circuitry 35 storestherein the coordinates of the corresponding landmark so as to be keptin correspondence with the identification code “V1” illustrated in FIG.7. Similarly, the storage circuitry 35 stores therein the identificationcodes and the coordinates of the landmarks so as to be kept incorrespondence with one another. Although FIG. 7 illustrates only thelungs, the heart, the liver, the stomach, and the kidneys as organs, thevirtual patient image in actuality further includes a large number oforgans, bonds, blood vessels, nerves, and the like. Further, althoughFIG. 7 illustrates only the landmarks corresponding to theidentification codes “V1”, “V2”, and “V3”, the virtual patient image inactuality includes a larger number of landmarks.

The position matching function 37 b brings the coordinate space of thevolume data into association with the coordinate space of the virtualpatient image, by matching the landmarks in the volume data of thepatient P detected by the detecting function 37 a with the landmarks inthe abovementioned virtual patient image, by using the identificationcodes. FIG. 8 is a drawing for explaining an example of the matchingprocess performed by the position matching function 37 b according tothe first embodiment. In this situation, FIG. 8 illustrates an examplein which the matching process is performed by using three sets oflandmarks to which identification codes are assigned so as to indicatemutually the same landmarks between the landmarks detected from ascanogram image and the landmarks detected from the virtual patientimage. However, possible embodiments are not limited to this example. Itis possible to perform the matching process by using any arbitrary setsof landmarks.

For example, as illustrated in FIG. 8, when matching the landmarksidentified with the identification codes “V1”, “V2”, and “V3” in thevirtual patient image, with the landmarks identified with theidentification codes “V1”, “V2” and “V3” in the scanogram image, theposition matching function 37 b brings the coordinate spaces of theimages in association with each other by performing a coordinatetransformation process so as to minimize positional deviations betweenthe pairs of mutually-the-same landmarks. For example, as illustrated inFIG. 8, the position matching function 37 b calculates a coordinatetransformation matrix “H” presented below, so as to minimize a sum “LS”of positional deviations between “V1 (x1,y1,z1) and C1 (X1,Y1,Z1)”,between “V2 (x2,y2,z2) and C2 (X2,Y2,Z2)”, and between “V3 (x3,y3,z3)and C3 (X3,Y3,Z3)” that are pairs of anatomically the same landmarks.LS=((X1,Y1,Z1)−H(x1,y1,z1))+((X2,Y2,Z2)−H(x2,y2,z2))+((X3,Y3,Z3)−H(x3,y3,z3))

By using the calculated coordinate transformation matrix “H”, theposition matching function 37 b is able to transform the scan rangedesignated in the virtual patient image into a scan range within theposition determining image. For example, by using the coordinatetransformation matrix “H”, the position matching function 37 b is ableto transform a scan range “SRV” designated in the virtual patient imageinto a scan range “SRC” within the position determining image, asillustrated in FIG. 8. FIG. 9 is a drawing illustrating an example ofthe scan range transformation process using the coordinatetransformation according to the first embodiment. For example, asillustrated in the virtual patient image in FIG. 9, when the operatorsets the scan range “SRV” in the virtual patient image, the positionmatching function 37 b transforms the set scan range “SRV” into the scanrange “SRC” in the scanogram image, by using the coordinatetransformation matrix explained above.

As a result, for example, the scan range “SRV” set in the virtualpatient image so as to include the landmark corresponding to theidentification code “Vn” is set into the scanogram image as beingtransformed into the scan range “SRC” including the identification code“Cn” corresponding to the same landmark. The coordinate transformationmatrix “H” explained above may be stored in the storage circuitry 35 foreach patient P so as to be read and used as necessary or may becalculated every time a scanogram image is acquired. As explainedherein, according to the first embodiment, by having the virtual patientimage displayed for the purpose of designating a range at the time of apre-set operation and planning a position and a range within the virtualpatient image, it is possible to automatically set the position and therange within the position determining image corresponding to the plannedposition and range by using numerical values, after taking the positiondetermining image (the scanogram image).

Returning to the description of FIG. 2, the controlling function 37 c isconfigured to determine an injection condition for the contrast agent tobe administered to the patient P. The controlling function 37 c will beexplained in detail later.

An overall configuration of the medical information processing system100 and the exemplary configuration of the X-ray CT apparatus 1according to the first embodiment have thus been explained. The X-ray CTapparatus 1 according to the first embodiment configured as describedabove improves the level of precision in setting an image takingposition or the like in advance, by transforming either a designatedscan position or a designated scan range, on the basis of a matchingresult between the anatomical landmarks in the virtual patient image,with the landmarks based on structuring members in the patient P withinthe image data taken by performing either the position determining scanor the contrast-enhanced scan.

In some situations, the X-ray CT apparatus 1 may perform acontrast-enhanced scan by administering a contrast agent to the patientP. In this regard, conventional X-ray CT apparatuses calculate theamount of the contrast agent to be administered, by using the height,the weight, a BMI value, and the like of the patient. The circulation ofa contrast agent in the human body is also dependent on the sizes oforgans and the amount of blood. For this reason, there are somesituations where it may not be possible to accurately calculate anoptimal amount of contrast agent by using only those factors such as theheight, the weight, and the BMI value.

To cope with those situations, the X-ray CT apparatus 1 according to thefirst embodiment is configured to detect a structuring member of thepatient P and to determine an injection condition for a contrast agentto be administered to the patient P for a contrast-enhanced scan, on thebasis of information about the detected structuring member. Thisfunction is realized by the controlling function 37 c. In the followingsections, the controlling function 37 c will be explained.

On the basis of the information about the structuring member, thecontrolling function 37 c determines the injection condition for thecontrast agent to be administered to the patient P for thecontrast-enhanced scan. In this situation, the structuring member is asite to be scanned in the contrast-enhanced scan. For example, as theinformation about the structuring member, the controlling function 37 cderives at least one element selected from among: information about thesize of an organ of the patient P, information about the surface area ofan organ of the patient P, information about muscle mass of the patientP, information about fat mass of the patient P, and information aboutskeletal mass of the patient P, and further calculates the amount of thecontrast agent to be administered to the patient P as the injectioncondition. In this situation, from a detection result obtained by thedetecting function 37 a, the controlling function 37 c derives theinformation about the structuring member in the patient. In other words,by using the detection result obtained by the detecting function 37 a,the controlling function 37 c derives at least one element selected fromamong: the information about the size of the organ of the patient P, theinformation about the surface area of the organ of the patient P, theinformation about the muscle mass of the patient P, the informationabout the fat mass of the patient P, and the information about theskeletal mass of the patient P.

More specifically, the controlling function 37 c derives the informationabout the size of the organ of the patient P, by calculating a totalnumber of pixels in the volume data corresponding to the organ of thepatient P extracted by the detecting function 37 a. Further, thecontrolling function 37 c derives the information about the surface areaof the organ of the patient P by calculating a total number of pixels ina surface region (an outline region) in the volume data corresponding tothe organ of the patient P extracted by the detecting function 37 a.Furthermore, the controlling function 37 c derives the information aboutthe skeletal mass of the patient P, by calculating a total number ofpixels in the volume data corresponding to the bones of the patient Pextracted by the detecting function 37 a.

Further, when deriving the information about the muscle mass of thepatient P or the information about the fat mass of the patient P, thecontrolling function 37 c performs the following process: Thecontrolling function 37 c identifies a region obtained by eliminatingthe bones, the organs, the blood vessels, the nerves, and the lumensdetected by the detecting function 37 a from the volume data, as aprocessing region. After that, the controlling function 37 c identifiesvolume data of a muscle region and volume data of a fat region, on thebasis of pixel values (CT values) in the processing region. In thissituation, for example, the controlling function 37 c identifies, fromamong the pixels in the processing region, such pixels of each of whichthe CT value falls in the range from 30 to 50 as pixels in the volumedata of the muscle region. Further, for example, the controllingfunction 37 c identifies, from among the pixels in the processingregion, such pixels of each of which the CT value falls in the rangefrom −100 to −50 as pixels in the volume data of the fat region. Afterthat, the controlling function 37 c derives the information about themuscle mass of the patient P, by calculating the number of pixels in thevolume data of the muscle region. Also, the controlling function 37 cderives the information about the fat mass of the patient P, bycalculating the number of pixels in the volume data of the fat region.In this situation, the controlling function 37 c may derive theinformation about the muscle mass of the patient P and the informationabout the fat mass of the patient P without using the detection resultobtained by the detecting function 37 a. In that situation, withoutidentifying the processing region, the controlling function 37 cidentifies the volume data of the muscle region and the volume data ofthe fat region from the entirety of the volume data, on the basis of thepixel values (the CT values).

In the following sections, an example will be explained in whichinformation about the size of an organ is derived as the informationabout a structuring member. Further, in the following sections, anexample in which the controlling function 37 c has derived the size ofthe liver will be explained. For example, the controlling function 37 cidentifies the liver by using a detection result obtained by thedetecting function 37 a and further derives the size of the liver.

Subsequently, on the basis of the derived size of the liver, thecontrolling function 37 c calculates the amount of the contrast agent tobe administered to the patient P for a contrast-enhanced scan. In thissituation, the controlling function 37 c calculates the amount of thecontrast agent by referring to reference information. The referenceinformation will be explained, with reference to FIG. 10. FIG. 10 is adrawing for explaining the first embodiment. As illustrated in FIG. 10,the reference information stores information in which “types of theorgan”, “sizes of the organ” and “amounts of the contrast agent” arekept in correspondence with one another.

FIG. 10 illustrates an example in which the “types of the organ” areeach indicated as the liver. The “sizes of the organ” in FIG. 10 areindicated as ranges of sizes of the organ. For example, under the “sizesof the organ”, values such as “X1 to X2”, “X2 to X3”, and so on arestored. In the present example, X1<X2<X3<X4<X5<X6 is satisfied. Further,the “amounts of the contrast agent” in FIG. 10 indicate differentamounts of the contrast agent to be administered depending on the sizeof the organ. For example, under the “amounts of the contrast agent”,values such as “0.90Y (ml)”, “Y (ml)”, and so on are stored. In oneexample, the reference information in FIG. 10 derives the amount of thecontrast agent as “0.90Y (ml)”, when the size of the organ derived byusing the detection result obtained by the detecting function 37 a fallsin the range of “X1 to X2”. Although FIG. 10 illustrates an example ofthe reference information for each type of organ, possible embodimentsare not limited to this example. For instance, the X-ray CT apparatus 1may store therein basic information of each type of organ, incorrespondence with either weight values or BMI values of the patient P.Further, with respect to the skeleton mass, the muscle mass, the fatmass, and the body surface area of the patient P, the X-ray CT apparatus1 also stores therein information in which, similarly, information abouteach of the structuring members is kept in correspondence with amountsof the contrast agent. Alternatively, the X-ray CT apparatus 1 may storetherein the reference information as mathematical functions.

FIG. 11 is a flowchart illustrating a processing procedure performed bythe X-ray CT apparatus 1 according to the first embodiment. FIG. 11illustrates the flowchart for explaining an operation performed by theX-ray CT apparatus 1 as a whole. The following explains which step inthe flowchart corresponds to each of the constituent elements.

Step S101 is a step realized by the input circuitry 31. At step S101,the input circuitry 31 receives a selection of a protocol pre-set. StepS102 is a step realized by the scan controlling circuitry 33. At stepS102, the scan controlling circuitry 33 performs a position determiningscan.

Step S103 is a step corresponding to the detecting function 37 a. StepS103 is a step at which the detecting function 37 a is realized as aresult of the processing circuitry 37 invoking and executing thepredetermined program corresponding to the detecting function 37 a fromthe storage circuitry 35. At step S103, the detecting function 37 aperforms an AL analysis on the position determining image.

Step S104 is a step corresponding to the position matching function 37b. Step S104 is a step at which the position matching function 37 b isrealized as a result of the processing circuitry 37 invoking andexecuting the predetermined program corresponding to the positionmatching function 37 b from the storage circuitry 35. At step S104, theposition matching function 37 b matches a result of the AL analysis withpre-set positions.

Steps S105 through S110 are steps corresponding to the controllingfunction 37 c. Steps S105 through S110 are steps in which thecontrolling function 37 c is realized as a result of the processingcircuitry 37 invoking and executing the predetermined programcorresponding to the controlling function 37 c from the storagecircuitry 35. At step S105, the controlling function 37 c estimates anoptimal value for the amount of the contrast agent for the image takingsite, by referring to a reference value corresponding to the imagetaking site. For example, the controlling function 37 c detects astructuring member of the patient P and further determines an injectioncondition for the contrast agent to be administered to the patient P fora contrast-enhanced scan, on the basis of the information about thedetected structuring member.

After that, at step S106, the controlling function 37 c compares a setcontrast agent amount with the estimated optimal value for the amount ofthe contrast agent. Subsequently, at step S107, the controlling function37 c judges whether or not the difference between the set contrast agentamount and the estimated optimal value for the amount of the contrastagent is within a threshold range. In this situation, when thecontrolling function 37 c has determined that the difference between theset contrast agent amount and the estimated optimal value for the amountof the contrast agent is within the threshold range (step S107: Yes),the process proceeds to step S111. On the contrary, when the controllingfunction 37 c has determined that the difference between the setcontrast agent amount and the estimated optimal value for the amount ofthe contrast agent is not within the threshold range (step S107: No),information is provided at step S108 to indicate that the amount of thecontrast agent should be changed. In other words, when having determinedthat the difference between the set contrast agent amount and theestimated optimal value for the amount of the contrast agent is notwithin the threshold range, the controlling function 37 c determinesthat the determined injection condition is different from the injectioncondition that was set in advance. Further, the controlling function 37c informs the operator that the determined injection condition isdifferent from the injection condition that was set in advance.

After that, at step S109, the controlling function 37 c judges whetherinformation indicating that the amount of the contrast agent should bechanged has been received. In this situation, when the controllingfunction 37 c has determined that no information indicating a change inthe amount of the contrast agent has been received (step S109: No), theprocess proceeds to step S111. On the contrary, when the controllingfunction 37 c has determined that information indicating a change in theamount of the contrast agent has been received (step S109: Yes), thecontrolling function 37 c updates the setting for the amount of thecontrast agent at step S110. For example, when having receivedinformation from the operator indicating that the injection conditionthat was set in advance should be changed to the determined injectioncondition, the controlling function 37 c configures the determinedinjection condition into the contrast agent injector.

Step S111 is a step realized by the scan controlling circuitry 33. Atstep S111, the scan controlling circuitry 33 judges whether or notinformation instructing execution of a contrast-enhanced scan has beenreceived. In this situation, when the scan controlling circuitry 33 hasdetermined that no information instructing execution of acontrast-enhanced scan has been received (step S111: No), the processproceeds to step S107. On the contrary, when the scan controllingcircuitry 33 has determined that information instructing execution of acontrast-enhanced scan has been received (step S111: Yes), acontrast-enhanced scan is performed at step S112.

As explained above, according to the first embodiment, the injectioncondition for the contrast agent to be administered to the patient P forthe contrast-enhanced scan is determined, on the basis of theinformation about the structuring member. For example, even when theweight of the patient P is heavy, the X-ray CT apparatus 1 according tothe first embodiment makes the amount of the contrast agent smaller thanthe reference value, when the site of which the contrast is to beenhanced is the liver, while the size of the liver of the patient P issmaller than the reference value. Conversely, even when the weight ofthe patient P is light, the X-ray CT apparatus 1 according to the firstembodiment makes the amount of the contrast agent larger than thereference value, when the site of which the contrast is to be enhancedis the liver, while the size of the liver of the patient P is largerthan the reference value. As another example, even when the physique ofthe patient P is large, the X-ray CT apparatus 1 according to the firstembodiment decreases the amount of the contrast agent when the musclemass is small while the fat mass is large and increases the amount ofthe contrast agent when the skeleton mass is large while the muscle massis large. With these arrangements, the operator is able to accuratelydetermine the amount of the contrast agent to be administered to thepatient P. As a result, according to the first embodiment, it ispossible to aid the viewer to interpret the image having high contrast,with a high level of precision.

In addition, as a result, according to the first embodiment, whileaiding the viewer to interpret the images with a high level ofprecision, it is also possible to suppress the amount of the contrastagent to be administered to the patient to a minimum necessary level.Consequently, it is possible to reduce burdens on the patient.

In the first embodiment above, the example is explained in which thecontrolling function 37 c is configured to inform the operator that thedetermined injection condition is different from the injection conditionthat was set in advance and to further configure the determinedinjection condition into the contrast agent injector when havingreceived the information from the operator indicating that the injectioncondition that was set in advance should be changed to the determinedinjection condition. However, possible embodiments are not limited tothis example. For instance, the controlling function 37 c may configurethe determined injection condition into the contrast agent injector,without informing the operator that the determined injection conditionis different from the injection condition that was set in advance orwithout receiving the information from the operator indicating thechange.

Second Embodiment

In the first embodiment, the example is explained in which one elementis derived as the information about a structuring member, and the amountof the contrast agent to be administered to the patient is calculated asthe injection condition. In this regard, the number of elements derivedas the information about structuring members may be two or more. Thus,in a second embodiment, an example will be explained in which two ormore elements are used as the information about the structuring members.

A configuration of an X-ray CT apparatus according to the secondembodiment is almost the same as the configuration of the X-ray CTapparatus 1 according to the first embodiment, except that a part of thefunctions of the controlling function 37 c is different. Thus, theexplanation about configurations other than the controlling function 37c will be omitted. When using a plurality of elements, the controllingfunction 37 c is configured to calculate a statistical value for theamount of the contrast agent to be administered to the patientcalculated for each of the plurality of elements, as the amount of thecontrast agent to be administered to the patient. FIG. 12 is a drawingfor explaining a second embodiment.

FIG. 12 illustrates an example in which “skeleton mass”, “muscle mass”,and “the size of the organ” are derived as the information aboutstructuring members, so that an amount of contrast agent is calculatedfor each of the derived elements. For example, on the basis of thederived “skeleton mass”, the controlling function 37 c calculates anamount of contrast agent as “1.10Y (ml)”. On the basis of the derived“muscle mass”, the controlling function 37 c calculates an amount ofcontrast agent as “0.90Y (ml)”. On the basis of the derived “size of theorgan”, the controlling function 37 c calculates an amount of contrastagent as “0.90Y (ml)”. Subsequently, the controlling function 37 ccalculates a statistical value for the calculated amounts of thecontrast agent to be administered to the patient P. For example, thecontrolling function 37 c calculates an average value of the amounts ofthe contrast agent as the amount of the contrast agent to beadministered to the patient P. In the example in FIG. 12, thecontrolling function 37 c calculates the amount of the contrast agent tobe administered as “0.97Y (ml)”. The controlling function 37 c maycalculate an average value after applying weights to the elements.

As explained above, according to the second embodiment, the X-ray CTapparatus 1 calculates the amount of the contrast agent to beadministered to the patient P, by using the plurality of elements as theinformation about the structuring members. With this arrangement,according to the second embodiment, it is possible to more accuratelydetermine the injection condition for the contrast agent to beadministered to the patient P.

In the second embodiment also, the example is explained in which thecontrolling function 37 c is configured to inform the operator that thedetermined injection condition is different from the injection conditionthat was set in advance and to further configure the determinedinjection condition into the contrast agent injector when havingreceived the information from the operator indicating that the injectioncondition that was set in advance should be changed to the determinedinjection condition. However, possible embodiments are not limited tothis example. For instance, the controlling function 37 c may configurethe determined injection condition into the contrast agent injector,without informing the operator that the determined injection conditionis different from the injection condition that was set in advance orwithout receiving the information from the operator indicating thechange.

Third Embodiment

In the first and the second embodiments above, the controlling function37 c is configured to determine the amount of the contrast agent, on thebasis of the information about the one or more structuring members.However, there are some situations where, when the speed of the bloodflow is high, it is not possible to enhance the contrast of a targetsubject to the contrast enhancement even with the injection of acontrast agent. To cope with these situations, an example will beexplained in a third embodiment in which at least one selected frombetween the concentration and the injection speed of the contrast agentto be administered to the patient is calculated as an injectioncondition.

A configuration of an X-ray CT apparatus according to the thirdembodiment is almost the same as the configuration of the X-ray CTapparatus 1 according to the first embodiment, except that a part of thefunctions of the controlling function 37 c is different. Thus, theexplanation about configurations other than the controlling function 37c will be omitted.

For example, the controlling function 37 c according to the thirdembodiment is configured to calculate, as an injection condition, atleast one selected from between the concentration and the injectionspeed of the contrast agent to be administered to the patient P, on thebasis of a scan condition and information about the size of the heartderived as information about a structuring member. In this situation,for example, the controlling function 37 c calculates the speed of theblood flow by deriving a cardiac ejection amount by performing a helicalscan so as to include various states corresponding to mutually-differentcardiac phases. After that, for example, when the degree of contrastenhancement is not sufficient for the organ subject to a contrastenhancement, the controlling function 37 c displays a comment in apop-up window indicating that the concentration of the contrast agentshould be increased or that the injection speed should be raised, sothat the contrast agent is injected at the same speed as the speed ofthe blood flow. After that, when having received information from theoperator indicating that the injection condition should be changed, thecontrolling function 37 c increases the concentration of the contrastagent or raises the injection speed. Alternatively, the controllingfunction 37 c may be configured to calculate the cardiac ejection amountfrom systolic and diastolic blood pressure values. With thesearrangements, according to the third embodiment, it is possible togenerate a reconstructed image having clear contrast, even when thespeed of the blood flow is high.

OTHER EMBODIMENTS

The first to the third embodiments have thus been explained. It is,however, possible to carry out the present disclosure in variousdifferent forms other than those described in the first to the thirdembodiments above.

The controlling function 37 c may be configured to obtain informationindicating sensitivity of the patient P to contrast agents and todetermine an injection condition for the contrast agent to beadministered to the patient P by referring to the obtained information.For example, the controlling function 37 c obtains, from the HIS,information indicating whether or not the patient is allergic tocontrast agents and kidney function information such as a creatine levelin the blood or the like. Further, when the patient P is allergic tocontrast agents or when the creatine value is equal to or larger than apredetermined threshold value, the controlling function 37 c alerts theoperator. FIG. 13 is a drawing for explaining this other embodiment.

FIG. 13 illustrates an example in which the patient P is allergic tocontrast agents. For example, to alert the operator, the controllingfunction 37 c displays in a pop-up window a message reading “<Caution>The patient is allergic to contrast agents”. Further, when havingalerted the operator, the controlling function 37 c may stop thecontrast agent injector from injecting the contrast agent.Alternatively, when having alerted the operator and having received aninstruction from the operator to perform a contrast-enhanced imagetaking process, the controlling function 37 c may limit the amount ofthe contrast agent so as to be injected only up to a predeterminedvolume set in advance.

Further, the controlling function 37 c may be configured to request amedical doctor in charge to approve of changing the injection conditionfor the contrast agent. For example, the controlling function 37 cgenerates an e-mail requesting an approval for a change in the injectioncondition for the contrast agent and sends the e-mail to the medicaldoctor in charge. Alternatively, the controlling function 37 c maycontact the medical doctor in charge via an intra-hospital telephoneline or the like to request an approval for a change in the injectioncondition for the contrast agent. In those situations, when havingreceived an approval from the medical doctor in charge, the controllingfunction 37 c changes the injection condition for the contrast agent. Inother words, the controlling function 37 c does not change the amount ofthe contrast agent configured in the contrast agent injector, until thecontrolling function 37 c receives an approval from the medical doctorin charge.

Further, as a result of the AL analysis, when the patient has only onekidney or only one lung or when the information about the size of anorgan exhibits a value equal to or smaller than a predeterminedreference value, there is a difference between the patient and thestandard human body model. In that situation, the controlling function37 c suppresses the injection condition for the contrast agent to beadministered to the patient P so as to be smaller than a predeterminedthreshold value. In other words, the controlling function 37 c derivesinformation about the size of the organ as the information about thestructuring member, and either when the information about the size ofthe organ exhibits a value equal to or smaller than the predeterminedreference value or when at least a part of the organ is missing, thecontrolling function 37 c suppresses the injection condition for thecontrast agent to be administered to the patient P so as to be smallerthan the predetermined threshold value. In addition, the X-ray CTapparatus 1 displays information indicating that the organ is missing inthe image of the virtual patient in a recognizable manner. For example,the X-ray CT apparatus 1 may display the missing organ by filling thearea with solid color or may add an annotation.

Further, when the determined injection condition has been used in acontrast-enhanced scan, the controlling function 37 c may be configuredto store the injection condition into a predetermined storage unit. Forexample, the X-ray CT apparatus 1 stores the injection condition for thecontrast agent into the HIS or the RIS. Further, the X-ray CT apparatus1 uses the injection condition for the contrast agent when performing animage taking process next time. Further, the X-ray CT apparatus 1 mayoutput the determined injection condition to an external apparatus.

In the embodiments described above, the example is explained in whichthe detecting function 37 a is configured to perform the AL analysis byusing either the volume data of the position determining image or thevolume data of the diagnosis-purpose image. However, possibleembodiments are not limited to this example. For instance, the detectingfunction 37 a may be configured to perform the AL analysis by using atwo-dimensional position determining image. Further, the detectingfunction 37 a may be configured to perform the AL analysis by usingimages that were taken in the past by the apparatus of its own for thepurpose of diagnosing the same patient. Alternatively, the detectingfunction 37 a may be configured to perform the AL analysis by usingmedical image data of the same patient that was taken by anotherapparatus.

Further, in the embodiments above, the X-ray CT apparatus is explainedas an example of a medical image taking apparatus; however, possibleembodiments are not limited to this example. For instance, the medicalimage taking apparatus may be an X-ray diagnosis apparatus, anultrasound diagnosis apparatus, a Magnetic Resonance Imaging (MRI)apparatus, or the like.

Further, in the embodiments above, the example is explained in which themedical image taking apparatus performs the process of determining theinjection condition for the contrast agent to be administered to thepatient P; however, possible embodiments are not limited to thisexample. For instance, it is acceptable to provide a medical imageprocessing apparatus or the like as a management apparatus, so that themanagement apparatus performs the process of determining the injectioncondition for the contrast agent to be administered to the patient P. Inother words, the management apparatus is configured to obtain image dataof the patient. Further, the management apparatus is configured todetect each of a plurality of sites of the patient from the image data.Further, the management apparatus is configured to subsequently deriveinformation about a structuring member in the patient on the basis ofthe detection result. Further, the management apparatus is configured todetermine the injection condition for the contrast agent to beadministered to the patient for a contrast-enhanced scan, on the basisof the information about the structuring member.

The term “processor” used in the explanation above denotes, for example,a circuit such as a Central Processing Unit (CPU), a Graphics ProcessingUnit (GPU), an Application Specific Integrated Circuit (ASIC), or aprogrammable logic device (e.g., a Simple Programmable Logic Device[SPLD], a Complex Programmable Logic Device [CPLD], or a FieldProgrammable Gate Array [FPGA]). Each of the processors realizes thefunction thereof by reading a program stored in the storage circuit andexecuting the read program. Alternatively, it is also acceptable todirectly incorporate the program into the circuit of each of theprocessors, instead of having the programs stored in the storagecircuit. In that situation, each of the processors realizes the functionthereof by reading the program incorporated in the circuit thereof andexecuting the read program. The processors according to the presentembodiments each do not necessarily have to individually be configuredas a single circuit. It is also acceptable to structure a singleprocessor by combining together a plurality of independent circuits soas to realize the functions thereof. Further, it is also acceptable tointegrate the plurality of constituent elements illustrated in FIG. 2into a single processor so as to realize the functions thereof.

The constituent elements of the apparatuses and the devices illustratedin the drawings in the embodiments above are based on functionalconcepts. Thus, it is not necessary to physically configure theconstituent elements as indicated in the drawings. In other words, thespecific modes of distribution and integration of the apparatuses andthe devices are not limited to those illustrated in the drawings. It isacceptable to functionally or physically distribute or integrate all ora part of the apparatuses and the devices in any arbitrary units,depending on various loads and the status of use. Further, all or anarbitrary part of the processing functions performed by the apparatusesand the devices may be realized by a CPU and a computer program analyzedand executed by the CPU or may be realized as hardware using wiredlogic.

Further, it is possible to realize the controlling method explained inthe first embodiment, by causing a computer such as a personal computeror a workstation to execute a control computer program (hereinafter,“control program”) prepared in advance. It is possible to distribute thecontrol program via a network such as the Internet. Further, the controlprogram may be executed as being recorded on a computer-readablerecording medium such as a hard disk, a flexible disk (FD), a CompactDisk Read-Only Memory (CD-ROM), a Magneto-Optical (MO) disk, a DigitalVersatile Disk (DVD), or the like and being read from the recordingmedium by a computer.

As explained above, according to at least one aspect of the embodiments,it is possible to accurately determine the injection condition for thecontrast agent to be administered to the patient.

While certain embodiments have been described, these embodiments havebeen presented by way of example only, and are not intended to limit thescope of the inventions. Indeed, the novel embodiments described hereinmay be embodied in a variety of other forms; furthermore, variousomissions, substitutions and changes in the form of the embodimentsdescribed herein may be made without departing from the spirit of theinventions. The accompanying claims and their equivalents are intendedto cover such forms or modifications as would fall within the scope andspirit of the inventions.

What is claimed is:
 1. A medical image diagnosis apparatus comprising:obtaining circuitry configured to obtain volume image data of a patient;detecting circuitry configured to detect each of a plurality of sites ofthe patient from the volume image data; and processing circuitryconfigured to: derive, on a basis of a detection result obtained by thedetecting circuitry, information about a structuring member in thepatient by deriving a plurality of elements selected from: a totalnumber of pixels included in an organ of the patient in the volume imagedata corresponding a three-dimensional size of the organ; a total numberof pixels in a surface region of the volume image data corresponding toa surface area of the organ of the patient; a number of pixels in thevolume image data corresponding to a muscle mass of the patient; anumber of pixels in the volume image data corresponding to a fat mass ofthe patient; and a total number of pixels in the volume image datacorresponding to a skeleton mass of the patient; calculate a statisticalvalue using each of the derived plurality of elements; and determine anamount of contrast agent to be administered to the patient for acontrast-enhanced scan, on a basis of the statistical value.
 2. Themedical image diagnosis apparatus according to claim 1, wherein thestructuring member is a site to be scanned in the contrast-enhancedscan.
 3. The medical image diagnosis apparatus according to claim 1,wherein the processing circuitry further calculates at least oneselected from between a concentration and an injection speed of thecontrast agent to be administered to the patient, on a basis of a scancondition and information about a size of a heart.
 4. The medical imagediagnosis apparatus according to claim 1, wherein the processingcircuitry obtains information indicating sensitivity of the patient tocontrast agents and determines the amount of contrast agent to beadministered to the patient by referring to the obtained information. 5.The medical image diagnosis apparatus according to claim 1, wherein theprocessing circuitry derives the total number of pixels included in theorgan in the volume image data corresponding to the three-dimensionalsize of the organ as the information about the structuring member, andeither when the total number of pixels included in the organ in thevolume image data corresponding to the three-dimensional size of theorgan exhibits a value equal to or smaller than a predeterminedreference value or when at least a part of the organ is missing, theprocessing circuitry determines the amount of contrast agent to beadministered to the patient so as to be smaller than a predeterminedthreshold value.
 6. The medical image diagnosis apparatus according toclaim 1, wherein the processing circuitry configures the determinedamount of contrast agent into a contrast agent injector.
 7. The medicalimage diagnosis apparatus according to claim 1, wherein, when thedetermined amount of contrast agent is different from an amount ofcontrast agent that was set in advance, the processing circuitry furtherinforms an operator.
 8. The medical image diagnosis apparatus accordingto claim 7, wherein, when having received information from the operatorindicating that the injection condition that was set in advance shouldbe changed to the determined amount of contrast agent, the processingcircuitry configures the determined amount of contrast agent into acontrast agent injector.
 9. The medical image diagnosis apparatusaccording to claim 1, wherein, when the determined amount of contrastagent has been used in the contrast-enhanced scan, the processingcircuitry stores the determined amount of contrast agent into a storagecircuitry.
 10. The medical image diagnosis apparatus according to claim1, wherein the processing circuitry is configured to derive pixel valuescorresponding to the muscle mass or the fat mass of the patient by:determining a first image region, eliminating at least one of bones,organs, blood vessels, nerves, and lumens from the first image region toproduce a second image region, and identifying volume data of muscles orfat on a basis of pixel values from the second image region.
 11. Themedical image diagnosis apparatus according to claim 1, wherein thedetermined amount of contrast agent comprises an administration amountof the contrast agent.
 12. A management apparatus comprising: obtainingcircuitry configured to obtain volume image data of a patient; detectingcircuitry configured to detect each of a plurality of sites of thepatient from the volume image data; and processing circuitry configuredto: derive, on a basis of a detection result obtained by the detectingcircuitry, information about a structuring member in the patient byderiving a plurality of elements selected from: a total number of pixelsincluded in an organ of the patient in the volume image datacorresponding a three-dimensional size of the organ; a total number ofpixels in a surface region of the volume image data corresponding to asurface area of the organ of the patient; a number of pixels in thevolume image data corresponding to a muscle mass of the patient; anumber of pixels in the volume image data corresponding to a fat mass ofthe patient; and a total number of pixels in the volume image datacorresponding to a skeleton mass of the patient; calculate a statisticalvalue using each of the derived plurality of elements; and determine aninjection condition for a contrast agent to be administered to thepatient for a contrast-enhanced scan, on a basis of the statisticalvalue.
 13. The management apparatus according to claim 12, wherein theprocessing circuitry is configured to derive pixel values correspondingto the muscle mass or the fat mass of the patient by: determining afirst image region, eliminating at least one of hones, organs, bloodvessels, nerves, and lumens from the first image region to produce asecond image region, and identifying volume data of muscles or fat on abasis of pixel values from the second image region.
 14. The managementapparatus according to claim 12, wherein the determined injectioncondition comprises an administration amount of the contrast agent.